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Title: The effect of timescales on wind farm power variability with nonlinear model predictive control: Variability reduction in wind farm model predictive control
Award ID(s):
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Wind Energy
Page Range / eLocation ID:
1891 to 1908
Medium: X
Sponsoring Org:
National Science Foundation
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  1. Abstract

    This paper presents a graph‐based dynamic yaw model to predict the dynamic response of the hub‐height velocities and the power of a wind farm to a change in yaw. The model builds on previous work where the turbines define the nodes of the graph and the edges represent the interactions between turbines. Advances associated with the dynamic yaw model include a novel analytical description of the deformation of wind turbine wakes under yaw to represent the velocity deficits and a more accurate representation of the interturbine travel time of wakes. The accuracy of the model is improved by coupling it with time‐ and space‐dependent estimates of the wind farm inflow based on real‐time data from the wind farm. The model is validated both statically and dynamically using large‐eddy simulations. An application of the model is presented that incorporates the model into an optimal control loop to control the farm power output.

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  2. null (Ed.)
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